03dc1891506e10052f4c7800088069ba1e804bed,cmaes/optim_par_L2M2019Ctrl.py,CMATrainPar,f,#CMATrainPar#Any#,70

Before Change

    def f(self, v_params):
        self.n_gen += 1
        v_cost = Parallel(n_jobs=N_PROC, timeout=TIMEOUT)\
        (delayed(f_ind)(self.n_gen, i, p, self.best_reward_par[i]) for i, p in enumerate(v_params))
        return v_cost

params = np.ones(45)

After Change

        (delayed(f_ind)(self.n_gen, i, p) for i, p in enumerate(v_params))

        for total_reward in v_total_reward:
            if self.best_total_reward  < total_reward:
                filename = "./optim_data/cma/" + trial_name + "best_w.txt"
                print("")
                print("----")
                print("update the best score!!!!")
                print("\tprev = %.8f" % self.best_total_reward )
                print("\tcurr = %.8f" % total_reward)
                print("\tsave to [%s]" % filename)
                print("----")
                print("")
                self.best_total_reward  = total_reward
                np.savetxt(filename, params)

        return -v_total_reward

if __name__ == "__main__":
    prob = CMATrainPar()

Instances